McConnaughy, Tim

McNutt, Steve

Miles, Christopher

A pragmatic guide to acing the AWS ANS-C01 exam

AWS Certified Advanced Networking – Specialty (ANS-C01) Certification Guide

Malavasi, Alexandre

A project-based guide to building web applications with ASP.NET Core 9 and JavaScript frameworks

Modern Full-Stack Web Development with ASP.NET Core

Despoudis, Theofanis

Build clean and scalable apps with proven patterns and expert insights

TypeScript 5 Design Patterns and Best Practices

Verma, Jatin

Build a solid foundation in Snowflake to pass the SnowPro Core exam on the first attempt

SnowPro Core Certification Study Guide

Mukherjee, Amit

Casalaina, Marco

Saladi, Adithya

A practical guide to unlocking generative AI-powered innovation with Azure OpenAI

Azure OpenAI Essentials

Loredo, Robert

Write your own practical quantum programs with Python

Learn Quantum Computing with Python and IBM Quantum

Najlaa, Najihah

Master video editing with expert tips, techniques, and workflows

The Complete Guide to Adobe Premiere Pro 2025

Makhija, Jagjeet Singh

Odunukwe, Charles

Boost your skills with expert insights and certification-ready strategies for Microsoft analytics

Implementing Analytics Solutions Using Microsoft Fabric—DP-600 Exam Study Guide

Belmansour, Tidjani

Brady, Damian

A step-by-step guide to developing cross-platform CLI apps—from coding and testing to deployment

Building CLI Applications with C# and .NET

Apperson, Lem

Weinberger, Jonathan

Leverage C# scripting in Unity to create immersive games and VR experiences

Unity 6 Game Development with C# Scripting

Build, scale, and secure machine learning systems and MLOps pipelines in production

Machine Learning Engineering on AWS

<span xml:lang="en">Machine Learning Engineering on AWS: Build, scale, and secure machine learning systems and MLOps pipelines in production</span>

Lat, Joshua Arvin

Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life cycleKey FeaturesGain practical knowledge of managing ML workloads on AWS using Amazon SageMaker, Amazon EKS, and moreUse container and serverless services to solve a variety of ML engineering requirementsDesign, build, and secure automated MLOps pipelines and workflows on AWSBook DescriptionThere is a growing need for professionals with experience in working on machine learning (ML) engineering requirements as well as those with knowledge of automating...

Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life...

Format

Machine Learning Engineering on AWS

Build, scale, and secure machine learning systems and MLOps pipelines in production

Joshua Arvin Lat

People Also Read